A Semi-Automatic Method To Segment The Left Atrium in MR Volumes With Varying Slice Numbers

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dc.authorid0000-0001-7153-7583en_US
dc.contributor.authorUslu, Fatmatülzehra
dc.contributor.authorVarela, Marta
dc.contributor.authorBharath, Anil A.
dc.date.accessioned2021-03-20T20:12:21Z
dc.date.available2021-03-20T20:12:21Z
dc.date.issued2020
dc.departmentBTÜ, Mühendislik ve Doğa Bilimleri Fakültesi, Elektrik Elektronik Mühendisliği Bölümüen_US
dc.description42nd Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC) -- JUL 20-24, 2020 -- Montreal, CANADAen_US
dc.description.abstractAtrial fibrillation (AF) is the most common sustained arrhythmia and is associated with dramatic increases in mortality and morbidity. Atrial cine MR images are increasingly used in the management of this condition, but there are few specific tools to aid in the segmentation of such data. Some characteristics of atrial cine MR (thick slices, variable number of slices in a volume) preclude the direct use of traditional segmentation tools. When combined with scarcity of labelled data and similarity of the intensity and texture of the left atrium (LA) to other cardiac structures, the segmentation of the LA in CINE MRI becomes a difficult task. To deal with these challenges, we propose a semi-automatic method to segment the left atrium (LA) in MR images, which requires an initial user click per volume. The manually given location information is used to generate a chamber location map to roughly locate the LA, which is then used as an input to a deep network with slightly over 0:5 million parameters. A tracking method is introduced to pass the location information across a volume and to remove unwanted structures in segmentation maps. According to the results of our experiments conducted in an in-house MRI dataset, the proposed method outperforms the U-Net [1] with a margin of 20 mm on Hausdorff distance and 0:17 on Dice score, with limited manual interaction.en_US
dc.description.sponsorshipIEEE Engn Med & Biol Socen_US
dc.description.sponsorshipWellcome/EPSRC Centre for Medical EngineeringUK Research & Innovation (UKRI)Engineering & Physical Sciences Research Council (EPSRC) [WT203148/Z/16/Z]; Medical Imaging Network [EP/N026993/1]; British Heart Foundation Centre of Research Excellence at Imperial College London [RE/18/4/34215]en_US
dc.description.sponsorshipThis research was supported by the Wellcome/EPSRC Centre for Medical Engineering [WT203148/Z/16/Z], the Medical Imaging Network (MedIAN) [EP/N026993/1] and the British Heart Foundation Centre of Research Excellence at Imperial College London [RE/18/4/34215].en_US
dc.identifier.endpage1202en_US
dc.identifier.isbn978-1-7281-1990-8
dc.identifier.issn1557-170X
dc.identifier.issn1558-4615
dc.identifier.pmid33018202en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage1198en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12885/495
dc.identifier.wosWOS:000621592201129en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakPubMeden_US
dc.institutionauthorUslu, Fatmatülzehra
dc.language.isoenen_US
dc.publisherIeeeen_US
dc.relation.ispartof42Nd Annual International Conferences Of The Ieee Engineering In Medicine And Biology Society: Enabling Innovative Technologies For Global Healthcare Embc'20en_US
dc.relation.ispartofseriesIEEE Engineering in Medicine and Biology Society Conference Proceedings
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subject[No Keywords]en_US
dc.titleA Semi-Automatic Method To Segment The Left Atrium in MR Volumes With Varying Slice Numbersen_US
dc.typeConference Objecten_US

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